Refinement of Multiconformer Ensemble Models from Multi-temperature X-ray Diffraction Data

Abstract

Conformational ensembles underlie all protein functions. Thus, acquiring atomic-level ensemble models that accurately represent conformational heterogeneity is vital to deepen our understanding of how proteins work. Modeling ensemble information from X-ray diffraction data has been challenging, as traditional cryo-crystallography restricts conformational variability while minimizing radiation damage. Recent advances have enabled the collection of high quality diffraction data at ambient temperatures, revealing innate conformational heterogeneity and temperature-driven changes. Here, we used diffraction datasets for Proteinase K collected at temperatures ranging from 313 to 363K to provide a tutorial for the refinement of multiconformer ensemble models. Integrating automated sampling and refinement tools with manual adjustments, we obtained multiconformer models that describe alternative backbone and sidechain conformations, their relative occupancies, and interconnections between conformers. Our models revealed extensive and diverse conformational changes across temperature, including increased bound peptide ligand occupancies, different Ca2+ binding site configurations and altered rotameric distributions. These insights emphasize the value and need for multiconformer model refinement to extract ensemble information from diffraction data and to understand ensemble-function relationships.

Protein conformational ensembles in function: roles and mechanisms

“…Equally so is the premise that conformational ensembles underlie all protein functions. 23,[55][56][57][58] The challenging aim facing the community is to elucidate the functions, especially how they are executed at the basic conformational level, and the mechanistic underpinnings of their signaling pathways. A conformational view is essential for in-depth comprehension of how proteins work and how they are regulated in the cell.…”

Functional Protein Dynamics in a Crystal

“…6 These snapshots represent ensemble averages, as proteins may adopt diverse conformations even within the crowded environment of a crystal. 8,9 Because of this conformational averaging, an ensemble view is needed to complement the dynamical information obtained in the EFX experiment.…”

“…30 Furthermore, protein conformational ensembles from crystalline MD simulations have recently been directly compared to multi-conformer ensemble models from x-ray diffraction. 9,32 Taken together, these methodological advances have set the stage to approach modeling non-equilibrium experiments using simulation.…”

“…6 These snapshots represent ensemble averages, as proteins may adopt diverse conformations even within the crowded environment of a crystal. 8,9 Because of this conformational averaging, an ensemble view is needed to complement the dynamical information obtained in the EFX experiment. Molecular dynamics (MD) simulations can explicitly probe conformational heterogeneity, describing protein motions with a high temporal resolution (femtoseconds) on timescales relevant to pump-probe experiments (ns to µ s).…”

Functional protein dynamics in a crystal

“…The latter, known as electric field-stimulated X-ray crystallography (EFX) can resolve protein dynamics on a sub-μs timescale by providing structural snapshots separated by 50 to 100 ns time intervals 6 . These snapshots represent ensemble averages, as proteins may adopt diverse conformations even within the crowded environment of a crystal 8,9 . Because of this conformational averaging, an ensemble view is needed to complement the dynamical information obtained in the EFX experiment.…”